Key result
Heart rate variability features from wearable ECG detected short-term memory deterioration under cold stress with 82.4% accuracy, outperforming electrodermal activity features (55.4% accuracy).
Why the study?
Prolonged cold-air exposure can impair cognitive function, and females are reported to be more sensitive to cold exposure, prompting investigation into whether physiological metrics can track cognitive performance deterioration under cold stress.
Can wearable ECG and EDA detect cognitive performance deterioration in females exposed to cold air?
Observational (n=19)
Can wearable ECG and EDA detect cognitive performance deterioration in females exposed to cold air?
Absolute Event Rate: 82.4% vs 55.4%
Wearable ECG-derived HRV features are more accurate than EDA features for detecting cognitive performance deterioration due to cold stress in females.
HRV-based models may flag cognitive decline risk in cold-exposed females; leaves open prospective validation before any clinical adoption.
Prolonged exposure to cold air can impair reaction time and cognitive function, which can lead to serious consequences. One mitigation strategy is to develop models that can predict cognitive performance by tracking physiological metrics associated with cold stress. As females are evidenced to be more sensitive to cold exposure, this study investigated the relationship between physiological metrics and cognitive performance deterioration of female subjects under cold stress. Wearable electrodermal activity (EDA) and electrocardiogram (ECG) were collected from nineteen females who underwent five sessions of a cognitive task battery-assessing reaction time, memory, and attention-in a cold (10 °C) environment. Machine learning classifiers showed higher cognitive performance classification accuracies with heart rate variability (HRV) features than with EDA features. Particularly in detecting performance deterioration in a task associated with assessing short-term memory, our support vector machine classifier with HRV features showed an 82.4% accuracy, with a sensitivity of 84.2% and a specificity of 80.6%, whereas a 55.4% accuracy with a sensitivity of 44.7% and a specificity of 66.7% was obtained with EDA features. Our results demonstrate the feasibility of detecting performance deterioration from females who underwent cold exposure using wearable EDA and ECG, allowing for preventive measures to reduce risk in cold environments, especially for female military personnel.
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Kong et al. (2025) conducted an observational in Cognitive performance deterioration due to cold stress (n=19). Heart rate variability (HRV) features from wearable ECG vs. Electrodermal activity (EDA) features was evaluated on Classification accuracy for detecting performance deterioration in a short-term memory task. Heart rate variability features from wearable ECG detected short-term memory deterioration under cold stress with 82.4% accuracy, outperforming electrodermal activity features (55.4% accuracy).
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